Ragie MCP Server

The Ragie Model Context Protocol (MCP) Server is a lightweight bridge that lets AI assistants—such as Claude or Cursor—tap directly into a Ragie knowledge base. By exposing a single, well‑defined tool named retrieve, the server solves the common problem of pulling up-to-date, domain‑specific information into an AI’s context without requiring custom integrations or manual data exports. Developers can now empower conversational agents to answer questions about internal policies, product specifications, or any other content stored in Ragie with minimal friction.

At its core, the server listens on standard input/output for MCP messages and forwards each retrieve request to Ragie’s API. The tool accepts a simple query string, an optional parameter to limit the number of results, and a boolean flag that can reorder hits by relevance. The response is returned as a structured JSON payload, ready for the AI to embed in its prompt or present directly to the user. This tight coupling means that every time a model needs fresh data, it can issue a single tool call and receive a curated set of documents in seconds.

Key features include:

• Customizable description – Developers can override the default tool description to match their workflow or company terminology.
• Partition awareness – By specifying a partition ID, the server can target specific subsets of a Ragie knowledge base, enabling multi‑tenant or role‑based access.
• Seamless integration with popular IDEs – The README outlines how to configure Cursor and Claude Desktop, turning the server into a first‑class component of the developer’s toolchain.
• Environment‑based authentication – Only an API key is required, which the server reads from , keeping credentials out of code.

Real‑world scenarios that benefit most from this server include:

• Enterprise support bots that need instant access to internal troubleshooting guides.
• Sales enablement assistants that pull product sheets or pricing tiers on demand.
• Compliance checkers that verify policy adherence by querying regulatory documents stored in Ragie.

By integrating the Ragie MCP Server into an AI workflow, developers gain a scalable, secure, and low‑maintenance method for enriching conversational agents with authoritative knowledge. The result is a more trustworthy assistant that can answer complex queries, reduce hallucinations, and keep users engaged with reliable information—all while preserving the agility of modern development environments.